计算机科学 ›› 2022, Vol. 49 ›› Issue (11): 335-344.doi: 10.11896/jsjkx.220300138
时坤1, 周勇1, 张启亮2, 姜顺荣1
SHI Kun1, ZHOU Yong1, ZHANG Qi-liang2, JIANG Shun-rong1
摘要: 区块链技术可以有效地解决分布式能源交易系统中的信任缺失、恶意篡改和虚假交易等问题,但区块链开放、透明的特性使得基于区块链的能源交易系统极易受到攻击,导致用户隐私泄露。为此,提出了一种基于差分隐私算法和账户映射技术的隐私保护方案BLDP-AM(Blockchain Local Differential Privacy-Account Mapping),用于保护交易数据的隐私。该方案重新设计了本地差分隐私算法的数据扰动机制使之适用于区块链技术,并基于该扰动机制构造了BLDP(Blockchain Local Differential Privacy)算法来保护交易数据的隐私。同时,为了保证交易正确性以及隐藏交易曲线特征,该方案首先通过账户映射(Account Mapping,AM)技术实现用户与多个账户关联,然后采用指数平滑预测(Exponential Smoothing Prediction,ESP)算法计算各账户的交易预测值,最后使用BLDP算法扰动交易预测值来获得真实交易值并进行交易。通过隐私分析证明了该方案在保护数据隐私方面的可行性,且实验分析表明该方案具有较好的性能。
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